Detection and treatment of cancer in early stages of tissue malignancy generally leads to a favorable result. In contrast, misdiagnosis and in particular a false positive diagnosis, often leads to unnecessary further testing and/or treatment that can be costly and harmful, resulting in pain and mental anguish for the patient.
The conventional approach to diagnosing suspect regions as lesions or nodules and ascertaining whether they are benign or malignant generally begins with imaging the suspect region using a non-invasive medical imaging technique. Examples of such imaging techniques include X-ray based techniques, such as computer aided tomography (CT) scans, and magnetic resonance imaging (MRI) scans. Inflamed tissues express stress hormones that induce the rapid but porous growth of capillaries to the inflammation site to assist healing. Poorly differentiated cancer lesions tend to grow initially without supporting capillaries. They come under stress for lack of nutrient delivery and waste removal (e.g. glucose and CO, respectively). The stress hormones emitted also result in porous capillary formations which leak contrast agents, such as iodine for CT scans and Gadolinium (Gd) for MRI scans, injected into the patient prior to performing the scan. The contrast enhanced images and other data from the scan is then evaluated by a trained clinician who provides a subjective assessment based on the visual inspection of whether the nodules are likely benign or malignant requiring further testing, such as a biopsy, or treatment. As already noted such testing can be time-consuming, costly and can be quite painful and result in mental anguish for the patient.
Accordingly, there is a need for a method of predicting the likelihood of a suspect nodule being malignant at early stage in testing to avoid unnecessary further testing or treatment. There is a further need for method of evaluating images and/or data that utilizes quantitative and numerical marker values to accurately screen and diagnose cancer nodules in patients, thereby reducing the need for subjective evaluation by highly trained and experienced professionals. It is further desirable that the method is capable of being automated.